¹ Published as a supplement to The Journal of
Nutrition. Guest editors for this supplement publication were Reynaldo
Martorell, The Rollins School of Public Health of Emory University, Atlanta, GA
and Nevin Scrimshaw, The United Nations University, Boston, MA.

The effect of early childhood nutritional supplementation on skeletal
maturation at adolescence was investigated in 663 rural Guatemalans, aged 1118
y. Skeletal maturation was assessed by the Tanner-Whitehouse-2 method. The
subjects were former participants in the Institute of Nutrition of Central
America and Panama longitudinal study of growth and development (1969-77)
residing in four villages (two large and two small) in eastern Guatemala. The
villages were randomized within pairs to receive either a high energy, high
protein supplement (Atole) or a low energy supplement with no protein (Fresco).
Skeletal maturity was observed across all villages to be delayed significantly
relative to a British reference for boys<14 y of age, but not for older boys
or for girls<14 y of age. Delays in girls>14 years could not be determined
reliably because many had reached maturity. Girls<14 years from Atole
villages were more advanced in skeletal maturity than similar age girls from
Fresco villages but these differences were found only in comparisons of the
large villages. The relationship between early nutrition and biological
maturation at adolescence may be obscured in this sample by the advanced age at
which the subjects were examined in adolescence. J. Nutr. 125:1097S-1103S,
1995.

More is known about the effects of early childhood protein-energy
malnutrition on growth than on biological maturation. Some studies have shown,
however, that early undernutrition delays maturation in both experimental
animals (Schroeder and Zeman 1973) and in humans (Alvear et al. 1986, Bailey et
al. 1984, Himes 1978). In the Institute of Nutrition of Central America and
Panama (INCAP) longitudinal study, maturation was assessed in preschool children
by counting the number of ossification centers present in a hand-wrist X-ray
(Yarbrough et al. 1973). Effects of nutritional supplementation on maturation
were found in both sexes but the differences were of lesser magnitude than those
seen on linear growth (Martorell et al. 1979). Approximately 20% of the effects
on linear growth could be attributed to accelerated maturation.

The long-term effects of malnutrition in early childhood on growth
and development at adolescence are less well known. Associations between
stunting in early childhood with patterns of growth in adoleence and with
attained adult height have been demonstrated (Billewicz and MacGregor 1982,
Hauspie et al. 1980, Satyanarayana et al. 1980, Satyanarayana et al. 1989).
Martorell et al. (1990) found that stunting in early childhood in rural
Guatemalans persisted into adolescence and that height gain between 5 and 18 y
of age was independent of height status at 5 y.

Satyanarayana et al. (1989) found that timing and duration of peak
height velocity in an Indian sample was dependent on the degree of stunting at 5
y of age. Cross-sectional studies from developing countries suggest that
nutritional status assessed by anthropometry during adolescence is related to
maturity indicators such as age at menarche, skeletal age (SA) and the
development of secondary sex characteristics (Spurr et al. 1983). However, it is
not known whether preschool-age delays in biological maturation related to
protein-energy malnutrition persists into adolescence. Biological maturation may
be an important mediating factor for the effects of early malnutrition on
growth, body composition, work capacity, activity and social development during
adolescence - all important outcomes examined in the INCAP follow-up study
reported in this volume.

The objective of this research is to assess the long term effects
of early childhood nutritional supplementation on biological maturation at
adolescence, indicated by SA. The effects of both supplement type
(protein-plus-energy vs. Energy) and quantity on maturation at adolescence are
investigated in a follow-up sample of the INCAP longitudinal study. Effects on
menarche are considered elsewhere (Khan et al.
1995).

Materials and methods

From 1969-77 INCAP conducted a longitudinal study of growth and
development with a nutrition intervention in four rural Guatemalan villages
(Martorell et al. 1995). The population was Ladino, or mixed Spanish and
Amerindian, heritage. Four villages were selected, stratified by size (i.e., two
had 900 people each and two had 500 people each) and randomly assigned to
receive one of two types of supplement. Two received Atole, which is a high
energy drink with a high protein content (163 kcal or 682 kJ plus 11.5 g protein
per cup or 180 mL) and two received Fresco, a low-energy drink with no protein
content (59 kcal or 247 kJ plus 0 g protein/180 mL). Consumption was ad libitum
but recording, daily to the nearest 10 mL, ceased when children reached 7 y of
age. As reported by Martorell et al. (1995), both supplements contained equal
amounts of selected micronutrients (iron, fluoride, riboflavin, niacin, thiamin,
ascorbic acid and vitamin Al, while the Atole also contained calcium and
phosphorus. Extensive growth and development data were collected in children
£7 y, including skeletal maturation, assessed by counting the number of
ossification centers present in a hand-wrist X-ray. At follow-up, during 1988
and 1989, researchers returned to the four study villages. All residents of the
four villages were considered potential subjects for the maturation study if
they had participated in the original INCAP study, were between 11 and 18 y of
age at follow-up and were nonpregnant. Coverage was 80% and the radiographic
sample for the four villages consisted of 883 subjects.

Hand-wrist X-rays were taken by trained INCAP field workers after
gaining informed parental consent and screening females of postmenarcheal status
for pregnancy. The radiographs were 8 x 10-inch anteriorposterior images of the
hand-wrist area, exposed through an intensifying screen using a portable X-ray
machine at a distance of 1 m. An adjustable columnator was used to reduce
scatter radiation. The radiation dosage received was 0.015 REM; allowable annual
exposure for the U.S. population is 0.5 REM beyond background radiation. The
research protocol was approved by the University Committees on Human Subjects
Research of Stanford and Cornell Universities and INCAP.

All radiographs were assessed in the field by one investigator
(K.E.P.). Skeletal maturation was assessed by the Tanner-Whitehouse-2 (TW2)
method (Tanner et al. 1983). The TW2 method involves the examination of 20 bones
of the hand and wrist and the assignment of a letter grade to each bone
dependent on the attainment of clearly described bone-specific maturity
indicators. The letter grade is then converted to a numeric score in accordance
with the tables given by Tanner et al. (1983) and the scores are summed for each
individual to give a maturity score on a scale of 0 to 1000. Maturity scores can
be converted to SA for each individual by comparison to British standards given
by Tanner et al. (1983) and the relative maturation can be assessed by
comparison of the SA to the individual's chronological age (CA). In this study
the radius-ulna-short bones (RUS) option of the TW2 method, using only the
radius, ulna and 11 short bones of the hand, was used to determine maturity
scores, SA and relative maturation. The carpal bones of the hand contribute
little to the assessment of skeletal maturation after the onset of puberty
(Johnston and Jahina 1965) and the RUS scheme therefore was more appropriate for
the assessment of variation in our sample of 11 - 18 my-old subjects. The
accuracy of the TW2 method is discussed by Tanner et al. (1983). Reliability,
composed of both precision and dependability, was assessed for the single
observer in this study as the coefficient of reliability (R2) in a
test-retest assessment of a random 10% of the sample radiographs (Marks et al.
1989). The coefficient of reliability was very high at 0.858. Of the 14.2%
unreliability estimate, 3.33% could be explained by the age of the subject, 1.1%
by the sex of the subject and 0.1% by the supplement group (Atole, Fresco) to
which the subject belonged.

For statistical analysis, the sample was divided into cohorts
corresponding to differential exposure to the nutrition intervention study in
early childhood (Martorell et al. 1995). The older cohort, Cohort 2, aged ~ 14-
18 y at follow-up, was exposed to the nutrition intervention in utero and from
birth to 3 y of age, the period considered most sensitive to the effects of the
nutrition intervention (Schroeder et al. 1995). After the age of 3 y these
subjects had variable exposure to the intervention, dependent on their age at
the end of the study in 1977. The subjects of the younger cohort, Cohort 1, aged
11-14 y at follow-up, had complete exposure in utero but variable age-dependent
exposure from birth to 3 y of age.

The outcome variable in all analyses was the SA deviation, or
relative maturation computed as SA -CA. Approximately 68% of the females in
Cohort a had reached skeletal maturity (SA = 15.9 y);in cases where CA was
³15.9 y, SA was set equal to CA and the SA deviation score was 0. A large
number of zero values accumulated at the higher ages of Cohort 2 and this
created analytical problems when testing for group differences in SA deviation
scores. Therefore, Cohort 2 females were excluded from the analysis reported in
this paper. In contrast, only 20% of the males in Cohort 2 had reached skeletal
maturity (SA = 18.0 y) while none had reached a CA of 18 y. Therefore, this
entire cohort was retained for analysis.

All statistical analyses were sex- and cohort-specific, with age
controlled within cohort. Sex specificity was essential due to sexual dimorphism
in skeletal maturation. CA was controlled in all within-cohort analyses because
SA deviation will regress naturally toward zero with advancing age.

The analysis was conducted in two stages. First, the effects of e
arly nutritional supplementation were assessed by comparing supplementation
groups (Atole vs. Fresco) using the GLM procedure of the SAS statistical package
(SAS Institute Inc. 1985) for analysis of covariance (ANCOVA). Analysis of
individual supplement intake followed, to establish the dose-response to early
supplementation in Atole male subjects in Cohort 2. This analysis was restricted
to Cohort 2 because most of the subjects in the younger cohort had<3 y of
exposure to the intervention and that exposure was confounded by age. Cohort 2,
on the other hand, was exposed to the intervention throughout gestation and the
first 3 y of life, with variable exposure thereafter, again depending on age.
Previous analysis (Schroeder et al. 1995) of anthropometry from this study has
shown that supplementation effects on linear growth are seen until 3 y of age
and not thereafter. Only Atole villages were used in analyses of dose-response
because the mean amount (110 kcal/d or 460 kJ/d) and range (0-366 kcal/d or
0-1531 kJ/d) of supplemental energy ingested was greater than in Fresco villages
(mean = 17 kcal/d or 71 kJ/d, range = 090 kcal/d or 0-377 kJ/d). Individual
supplemental energy intake was used as a continuous independent variable in a
multiple regression model using the REG procedure, after controlling for
socioeconomic status and village size in an ANCOVA model using the GLM
procedure. Several indicators of household socioeconomic status relating to
quality of house construction and household material possessions were measured
in 1975 and included in a factor analysis (see Rivera et al. 1995) to create a
general socioeconomic index. The resulting factor score (SES) was evaluated as a
possible confounder in all analyses. Statistical interactions between
supplementation group and village size were tested also.

Descriptive statistics of biological maturation measures for the
study sample are presented in Table 1. For comparison, both the 20-bone
and RUS SA are reported. The RUS ages are somewhat greater and more variable
than the 20-bone ages; however, the differences are not statistically
significant (paired t test). Deviation of the RUS SA from CA suggests a
significant (P<0.001) delay in skeletal maturity in the younger cohort of
males of 1.20 y, with a lesser delay (P>0.05) of 0.16 y in older males, and
no significant delay in females from Cohort 1.

TABLE 1 Descriptive statictis of skeletal maturity
indicators and other variables among male adolescents in cohorts 1 and 2 and
female adolescents in cohort 1¹

Age-adjusted mean and SE for the difference between SA and CA (SA
deviation) are presented for each sex and cohort for the Atole and Fresco groups
in Figure 1. The results of regression analysis that support this figure
are seen in Table 2. The Atole-Fresco differences were tested after
controlling for age and village size (large vs. small). Among males, there are
no significant Atole-Fresco differences in SA deviation for either cohort. Among
females from Cohort 1, the expected trend of Atole subjects being more mature
than Fresco subjects is statistically significant (Difference between Atole and
Fresco means = 0.39 y, t = 2. 13, P = 0.035).

FIGURE 1 Atole and
Fresco differences in the deviation of SA from CA among male and female
Guatemalan adolescents. Height of the bars represent means after adjusting for
age and village size (see Table 2). Brackets represent SE. Sample size for each
sample in parenthesis. P values are for test of Atole-Fresco differences in SA
deviation on a twosided test after controlling for age and village size.

The analysis was expanded to include socioeconomic status (SES) as
a potential confounder of the supplementation effect on SA deviation. Cohort 1
boys and girls from Atole villages had a tendency towards higher SES scores
(i.e., higher socioeconomic status) than their age mates from Fresco villages
(P<0.10). Moreover, SES scores tended to be associated positively with SA
deviation (P<0. 10), thus fulfilling the two criteria for confounding. When
SES was entered as a covariate into the basic models for Cohort l presented in
Table 2, the Atole-Fresco main effects were not changed for males but were
reduced slightly from 0.39 to 0.33 y for females, with the statistical
significance changing from P = 0.035 to 0.096. In Cohort males the SES scores
were similar in Atole and Fresco subjects and tended to be related to the SA
deviation (P = 0.065). Inclusion of SES in the models for this older male cohort
did not affect the Atole-Fresco differences reported in Table 2.

The interaction between village size and supplementation was
tested for each sex and cohort group with SES also included in the models.
Table 3 summarizes the results of the regression analysis that includes
this interaction. Atole exposure was associated with earlier maturation only in
the larger villages. The interaction was statistically significant for females
in Cohort 1 and males in Cohort 2. Among Cohort 1 females, who also had the only
significant main effect (Table 2) of supplement, Atole subjects were 0.94 y more
advanced than the Fresco subjects in the large villages but were 0.39 y behind
in the small villages.

TABLE 3 Summary of regression analysis of
supplementation effects on SA deviation by cohort, sex and village size
controlling for age and SES¹

To measure the dose-response of adolescent maturation, we
investigated the relationship between SA deviation and total supplemental energy
intake from birth to 3 y of age in Cohort 2 males from Atole villages (Table
4). After controlling for age, village size and SES, the effects of
supplemental energy intake was not significant.

TABLE 4 Regression analysis of amount of energy
consumed per day from Atole and SA deviation in Cohort 2 males¹

It is important to note that the sample sizes reported in Tables l
and 2 are reduced by ~ l 0% for any analysis that includes SES (Tables 3 and 4)
because of missing values. The descriptive statistics reported in Table l are
essentially the same when repeated on the reduced sample of subjects with SES
data.

Discussion

We hypothesized that nutritional supplementation in early
childhood would affect positively skeletal maturation status at adolescence.
Specifically, we hypothesized that subjects supplemented with the high energy,
high protein Atole would be advanced in maturation at adolescence compared with
subjects who received the low energy, no protein Fresco supplement. As further
support of the supplementation effect, we hypothesized that maturation at
adolescence would show a dose-response to the amount of supplemental energy
ingested in the first 3 y of life. We found only minimal support for these
hypotheses. Atole-Fresco differences in maturation status were small (0.4 y) and
restricted to the youngest cohort of girls between 11 and 14 y of age; also,
these weak effects were attenuated after controlling for SES. No linear
dose-response to individual supplemental energy intake was observed in the only
group suitable for testing this relationship: Cohort 2 males from the Atole
villages. These findings differ to some extent from those of Khan et al. (1995)
who found that the mean age at menarche was similar in Atole (13.75 ± 1.22
y) and Fresco (13.74 ± 1.75 y) villages. Thus, taken together, the studies
of skeletal maturation and of menarche suggest that the effect of improved
nutrition in childhood on maturation in adolescence is weak to absent.

As the results differ in some respects from our expectations, it
is necessary to seek an explanation of our findings by examining both our
original hypotheses and the various factors that may have caused the
nonsignificant results of this study: sample size, study design and the
influence of negative confounders.

The indicator of biological maturation chosen for this study was
skeletal maturation, which is sensitive to the effects of early undernutrition.
Martorell et al. (1979) reported a significant impact of the INCAP nutrition
intervention (of both type and amount of supplementation) on skeletal
maturation, measured by the number of hand-wrist ossification centers present in
early childhood (12-36 mo). We measured skeletal maturation by the RUS option of
the TW2 method,which can be used over the entire developmental period and is a
more accurate and precise measure of variation in maturation at adolescence than
alternative atlas methods, such as that of Greulich and Pyle (1959). The TW2
system allows for population variation in the pattern of maturation (Shakir and
Zaini 1974), is robust to minor assessment problems (Van Venrooij and Van
Ipenburg 1978) and assessment is neither agenor sex-dependent (Wenzel et al.
1984). In addition, the use of the RUS option allows the exclusion of the carpal
bones, problematic in the adolescent age range corresponding to this sample
(Johnston and Jahina 1965).

Sample sizes for Cohorts 1 and 2 of males were 220 and 223,
respectively, and 220 for Cohort 1 females. SD for the mean deviation in
maturation (SA deviation) of the three groups were 1.80, 1.32, and 1.41 y,
respectively. Using a statistical power (1 - b) of 0.90 and a P value
(a) of 0.05 to estimate z = 6.6 for a twotailed test (Snedecor and Cochran
1980), we can calculate the minimum difference (d) in SA deviation that
could have been detected in this study. Solving the equation

separately for males and females of each cohort shows that sample
size was sufficient to detect significant differences in the delay of maturation
between the Atole and Fresco groups as small as 0.43 and 0.32 y in males of each
cohort and 0.30 y in females of Cohort 1. This suggests that sample sizes within
each cohort by sex group were marginally adequate to detect differences of
biological significance (0.3-0.5 y).

It is probable that CA is acting as a negative confounder of the
effects of early supplementation on adolescent skeletal maturation at the time
of follow-up, as the age range of the subjects is 11-18 y. In wellnourished
populations, skeletal maturity is reached around the age of 16 in females and 18
in males. As the skeleton approaches full maturity, SA converges with CA to
reach zero difference at the completion of maturation. The variation in relative
maturation status (SA deviation) used as an outcome in this study therefore
decreases with age. This may explain the failure to show any dose-response in
the older cohort of males. For the test of Atole-Fresco differences in each
cohort, CA, along with other potential confounding factors such as village size
and sex, are controlled in each analysis. But lack of variation in SA deviation
in the older cohort cannot be corrected by controlling for confounders.

Cohort 1, the youngest group, had shorter, although variable,
exposure to the nutrition intervention than Cohort 2 and was not expected to
provide strong evidence of supplement effects on maturation at adolescence.
Therefore, it is somewhat surprising that the only significant supplementation
effect was seen in this younger cohort. However, it is also likely that even a
limited exposure to the Atole supplement has a significant effect on skeletal
maturation. Martorell et al. (1979) found a significant difference in the number
of hand-wrist ossification centers between Atole and Fresco male infants as
young as 12 mo of age and female infants as young as 24 mot Considering that the
better test of any supplementation effect is likely to be in younger rather than
older adolescents because of the age confounding effect discussed above, the
carryover into early adolescence of the early supplementation effects seen in
the first 2 y is plausible.

The interaction between village size and supplement group is
statistically significant (P = 0.016) for Cohort 2 boys but weaker in Cohort 1
boys (P = 0.22). A significant interaction also is seen in Cohort 1 girls
(P<0.001). We observed a greater positive effect of Atole supplementation in
large compared with small villages. Large villages were more delayed in skeletal
ma turity than small villages (Table 2). This might be interpreted as a greater
potential for the intervention to have been effective in groups where the
maturation process was more delayed. We have no explanation for the apparent
negative effect of Atole in the small villages, especially in Cohort 2 males.

The possible persistence into adolescence of a small and selective
effect of supplementation on skeletal maturity while the supplementation effects
on height remain about the same as seen at 3 y (Rivera et al. 1995) suggests
that the effect of delaying maturity to allow more time for catch-up growth is
minimal in this population.

In conclusion, we found that type of early nutritional
supplementation significantly affected skeletal maturation at adolescence, but
its effect was restricted to females <14 y of age and in large villages. It
is probable that the interpretation of results of this study are obscured by the
advanced age of most of the subjects at the time of the measurement of skeletal
maturation in adolescence. A study with a similar research design and that
follows up youth and adolescents at a somewhat younger age would help to
establish whether early nutritional supplementation affects maturation at
adolescence. Given the central importance of maturation status in explaining
variation in physical growth and performance, particularly at adolescence, and
the possibility that maturation acts as a mediator of long-term nutritional
effects on such outcomes, the relationship of early nutrition to later
biological maturation is worthy of further attention.